Triple
T11122897
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Black Widow (comics) |
E263060
|
entity |
| Predicate | protagonistCitizenship |
P14334
|
FINISHED |
| Object | Russian |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Russian | Statement: [Black Widow (comics), protagonistCitizenship, Russian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: protagonistCitizenship Context triple: [Black Widow (comics), protagonistCitizenship, Russian]
-
A.
protagonistJurisdiction
Indicates that a protagonist has legal authority, control, or official responsibility over a particular domain, area, or set of matters.
-
B.
protagonistNationality
chosen
Indicates the country or national identity to which the protagonist of a work is associated or belongs.
-
C.
protagonistAllegiance
Indicates the group, cause, or side with which the main character is aligned or to which they show loyalty.
-
D.
citizenTrait
Indicates that a particular trait, characteristic, or attribute is associated with a citizen in the context of the relationship.
-
E.
fictionalCitizenship
Indicates that an entity is recognized as a citizen of a fictional or imaginary polity, realm, or jurisdiction.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d6aa9b46cc8190b19f9f0cc45bf322 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7e82e933481908550499cf9dd6531 |
completed | April 9, 2026, 5:55 p.m. |
| PD | Predicate disambiguation | batch_69d7441efe948190ae4ab020121e169d |
completed | April 9, 2026, 6:15 a.m. |
Created at: April 8, 2026, 9:28 p.m.